check_token_riskReturns a 0-100 safety score, on-chain insider wallet clusters (wallets sharing a first funder), mint/freeze authority status, holder concentration, and live price/liquidity/volume for a single Solana token mint. Use before recommending or executing a trade on any Solana token. 5 free MCP calls/day, no signup. Then email key or x402.
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | The Solana token mint address to check |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It does this well by specifying the 0-100 score range, the data dimensions returned, and the quota/auth model ('5 free MCP calls/day, no signup. Then email key or x402'). It leaves failure modes or interpretation thresholds unstated, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences carry a substantial amount of useful information: output summary, call trigger, quota, and auth next step. The phrase 'Then email key or x402' is slightly cryptic but not bloated. Structure is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description supplies the key return categories and the invocation context, which is strong coverage for a single-parameter read-style tool. It could go further by explaining how to interpret the 0-100 score or what happens on invalid mints, but it is not incomplete enough to warrant a lower score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for the only parameter, mint, is 100%, so the schema already defines it as 'The Solana token mint address to check.' The description reinforces 'single Solana token mint' but adds no new format, validation, or usage nuance. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Returns') tied to a concrete resource ('a single Solana token mint') and enumerates the outputs: safety score, insider clusters, authority status, holder concentration, and price/liquidity/volume. It also implicitly differentiates from siblings (batch, history) via the 'single token' scoping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear trigger: 'Use before recommending or executing a trade on any Solana token.' It does not explicitly name when to choose batch or history alternatives, but the 'single token' phrasing signals the boundary. There are no misleading exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a clearly distinct operation: live single-mint risk check, batched multi-mint risk check, and historical risk data retrieval. The single vs. batch distinction is explicit in the names and descriptions, so there is no meaningful overlap or selection ambiguity.
All tools follow a consistent snake_case verb_noun pattern (check_token_risk, check_token_risk_batch, get_token_risk_history). The 'batch' suffix clearly modifies the object, and the switch from 'check' to 'get' appropriately distinguishes live assessment from historical data.
Three tools is lean but well-scoped for a focused token-risk API: a single check, a batch check, and a history lookup. Each tool fills a distinct role with no redundant or filler endpoints.
The core workflow—assess one token, assess many tokens, retrieve history—is fully covered. Minor gaps exist, such as no way to query remaining quota/credit before a batch call and no token metadata/lookup endpoint, but agents can work around these.